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Paper Citation Record · LEDGER

VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2501.06553.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.06553 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:04:29.736634Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T12:33:32.822605Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2cc535b5-af21-4378-8244-affaa988e455 · inbound

Hallucination of Multimodal Large Language Models: A Survey cites this paper.

Hallucination of Multimodal Large Language Models: A Survey VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification

Reference 237

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:33:32.840619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T12:33:32.631346Z digest=sha256:2002d690f06e998f56dbf264706b1ea4f73101104bc42ea28539bfaf219a37d1

Observation 92a36130-2c45-45bc-ac40-cf254b3a3596 · inbound

Do we really have to filter out random noise in pre-training data for language models? cites this paper.

Do we really have to filter out random noise in pre-training data for language models? VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-08T15:04:29.736634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:04:29.736634Z digest=sha256:3c2172c704617ae9e6befb7dba8ab6fa6e0f8da33562ff748a15b0ecb2fd286d

Observation 6a285e31-6ff6-44a6-83f3-f8e58b735e75 · inbound

Not All Tokens and Heads Are Equally Important: Dual-Level Attention Intervention for Hallucination Mitigation cites this paper.

Not All Tokens and Heads Are Equally Important: Dual-Level Attention Intervention for Hallucination Mitigation VASparse: Towards Efficient Visual Hallucination Mitigation via Visual-Aware Token Sparsification

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T00:53:27.008416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:53:27.008416Z digest=sha256:45945cc32e63fc5dccb9b54ad76595c90f5efb7ca18e131e678916b79662c7d2